A Context-Based Computational Model Of Language Aquisition By
Infants
And Children – Steven Walzak (springerlink)

A common motivation behind many approaches to context are: first, their
properties are specified using a top-down ‘design stance’ and second,
they
assume that the appropriate notions of context are general. In other
words,
they involve essentially guessing at the properties of the relevant
contexts
without any recognition that these properties might themselves be
context-specific.

In this special issue, we have tried to focus attention upon the
opposite
approach. We assume that the world is, to a large extent, a messy
and contingent place. This means that the transfer of knowledge
from
learning to application is only possible by a diverse collection of
heuristics
which exploit a heterogeneous set of commonalities which occur for a
variety
of reasons in different domains.

The alternative approach is to: search for local commonalities and
heuristics
in particular contexts and see how they can be utilised to produce
useful
techniques. Later some careful and incremental generalisation
might
turn out to be possible. In this way, we can truly start to ‘map out’
the
practical limits of generality using context-like constructs and maybe
avoid deceiving ourselves with overambitious schemes which later fail
to
scale up. This special issue includes half a dozen papers exemplifying
this approach.